AlexNet3D
3D Conv Net
An implementation of a 3D convolutional neural network based on the AlexNet architecture for image recognition in 3D data.
This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).
43 stars
5 watching
13 forks
Language: Python
last commit: almost 7 years ago
Linked from 1 awesome list
jtoy/awesome-tensorflowRelated projects:
| Repository | Description | Stars |
|---|---|---|
 forresti/squeezenet | Provides pre-trained models and training configurations for a deep neural network architecture optimized for image classification tasks | 2,176 |
 alexbrillant/multi-layer-perceptron | An implementation of a multi-layer neural network in Python, allowing users to train and use the network for classification tasks. | 5 |
 andreasveit/convnet-aig | An implementation of an adaptive neural network architecture that dynamically defines its topology based on input images. | 185 |
 xuzhenqi/cnn | Provides an implementation of convolutional neural networks in MATLAB. | 95 |
 ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 426 |
 hasnainraz/fc-densenet-tensorflow | Re-implementation of a 100-layer fully convolutional network architecture for image segmentation | 123 |
 yunishi3/3d-fcr-alphagan | This project aims to develop a generative model for 3D multi-object scenes using a novel network architecture inspired by auto-encoding and generative adversarial networks. | 103 |
 bruinxiong/modified-crunet-and-residual-attention-network.mxnet | An MXNet implementation of a modified deep neural network architecture for image classification | 67 |
 chenxi116/pnasnet.tf | An implementation of PNASNet-5 architecture in TensorFlow for image classification on ImageNet. | 102 |
 astorfi/3d-convolutional-speaker-recognition | Develops deep learning models using 3D convolutional neural networks for speaker verification tasks | 783 |
| bruinxiong/senet.mxnet | An implementation of Squeeze-and-Excitation Networks in MXNet for image classification tasks. | 154 |
 liqimai/gcn | An implementation of graph convolutional networks for semi-supervised learning in Python using TensorFlow and other libraries. | 45 |
 hassony2/inflated_convnets_pytorch | Creates inflated versions of 2D neural networks with transferred ImageNet weights for use in 3D applications | 148 |
 homles11/igcv3 | An implementation of an efficient deep neural network architecture | 189 |
 torontodeeplearning/convnet | A high-performance GPU implementation of neural networks using C++ | 506 |